Cumulative/dynamic ROC curve estimation

• Published in: Journal of statistical computation and simulation Vol. 86; no. 17; pp. 3582 - 3594
• Main Authors: Martínez-Camblor, Pablo, Bayón, Gustavo F., Pérez-Fernández, Sonia
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 21.11.2016; Taylor & Francis Ltd
• Subjects: Approximation; censored data; Censorship; Computer simulation; Cox regression model; Cumulative/dynamic ROC curve; Diagnostic systems; Dynamics; Estimators; Mathematical analysis; Monte Carlo simulation; Receivers; sensitivity; Sensitivity analysis; specificity; Time dependence
• ISSN: 0094-9655; 1563-5163
• DOI: 10.1080/00949655.2016.1175442

Receiver operating-characteristic (ROC) curve is a popular graphical method frequently used in order to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, the direct generalization is known as cumulative/dynamic ROC curve. For a fixed point of time, t, one subject is allocated into the positive group if the event happens before t and into the negative group if the event is not happened at t. The presence of censored subject, which can not be directly assigned into a group, is the main handicap of this approach. The proposed cumulative/dynamic ROC curve estimator assigns a probability to belong to the negative (positive) group to the subjects censored previously to t. The performance of the resulting estimator is studied from Monte Carlo simulations. Some real-world applications are reported. Results suggest that the new estimators provide a good approximation to the real cumulative/dynamic ROC curve.